Channels & Keyframes
CSE169: Computer Animation
Instructor: Steve Rotenberg
UCSD, Spring 2016
Animation
Rigging and Animation
Animation
System
Pose
Rigging
System
Triangles
Renderer
N ...21
Animation
When we speak of an animation, we refer to the data required to pose a rig over some range of time
This should include information to specify all necessary DOF values over the entire time range
Sometimes, this is referred to as a clip or even a move (as animation can be ambiguous)
Pose Space
If a character has N DOFs, then a pose can be thought of as a point in N-dimensional pose space
An animation can be thought of as a point moving through pose space, or alternately as a fixed curve in pose space
One-shot animations are an open curve, while loop animations form a closed loop
Generally, we think of an individual animation as being a continuous curve, but theres no strict reason why we couldnt have discontinuities (cuts)
N ...21
t
Channels
If the entire animation is an N-dimensional curve in pose space, we can separate that into N 1-dimensional curves, one for each DOF
We call these channels
A channel stores the value of a scalar function over some 1D domain (either finite or infinite)
A channel will refer to pre-recorded or pre-animated data for a DOF, and does not refer to the more general case of a DOF changing over time (which includes physics, procedural animation)
tii
Channels
tmin tmax
Time
Value
Channels
As a channel represents pre-recorded data, evaluating the channel for a particular value of t should always return the same result
We allow channels to be discontinuous in value, but not in time
Most of the time, a channel will be used to represent a DOF changing over time, but occasionally, we will use the same technology to relate some arbitrary variable to some other arbitrary variable (i.e., torque vs. RPM curve of an engine)
Array of Channels
An animation can be stored as an array of channels
A simple means of storing a channel is as an array of regularly spaced samples in time
Using this idea, one can store an animation as a 2D array of floats (NumDOFs x NumFrames)
However, if one wanted to use some other means of storing a channel, they could still store an animation as an array of channels, where each channel is responsible for storing data however it wants
Array of Poses
An alternative way to store an animation is
as an array of poses
This also forms a 2D array of floats
(NumFrames x NumDOFs)
Which is better, poses or channels?
Poses vs. Channels
Which is better?
It depends on your requirements.
The bottom line:
Poses are faster
Channels are far more flexible and can
potentially use less memory
Array of Poses
The array of poses method is about the
fastest possible way to playback animation
data
A pose (vector of floats) is exactly what
one needs in order to pose a rig
Data is contiguous in memory, and can all
be directly accessed from one address
Array of Channels
As each channel is stored independently, they have the flexibility to take advantage of different storage options and maximize memory efficiency
Also, in an interactive editing situation, new channels can be independently created and manipulated
However, they need to be independently evaluated to access the current frame, which takes time and implies discontinuous memory access
Poses vs. Channels
Array of poses is great if you just need to play back some relatively simple animation and you need maximum performance. This corresponds to many video games
Array of channels is essential if you want flexibility for an animation system or are interested in generality over raw performance
Array of channels can also be useful in more sophisticated game situations or in cases where memory is more critical than CPU performance (which is not uncommon)
Channels
As the array of poses method is very
simple, theres not much more to say
about it
Therefore, we will concentrate on
channels on their various storage and
manipulation techniques
Temporal Continuity
Sometimes, we think of animations as having a particular frame rate (i.e., 30 fps)
Its often a better idea to think of them as being continuous in time and not tied to any particular rate. Some reasons include: Film / NTSC / PAL conversion
On-the-fly manipulation (stretching/shrinking in time)
Motion blur
Certain effects (and fast motions) may require one to be really aware of individual frames though
Animation Storage
Regardless of whether one thinks of an animation as being continuous or as having discrete points, one must consider methods of storing animation data
Some of these methods may require some sort of temporal discretization, while others will not
Even when we do store a channel on frame increments, its still nice to think of it as a continuous function interpolating the time between frames
Animation Class
class AnimationClip {
void Evaluate(float time,Pose &p);
bool Load(const char *filename);
};
class Channel {
float Evaluate(float time);
bool Load(FILE*);
};
Channel Storage
There are several ways to store channels. Most approaches fall into either storing them in a raw frame method, or as piecewise interpolating curves (keyframes)
A third alternative is as a user supplied expression, which is just an arbitrary math function. In practice, this is not too common, but can be handy in some situations.
One could also apply various interpolation schemes, but most channel methods are designed more around user interactivity
Raw Data Formats
Sometimes, channels are stored simply as an array of values, regularly spaced in time at some frame rate
They can use linear or smoother interpolation to evaluate the curve between sample points
The values are generally floats, but could be compressed more if desired
The frame rate is usually similar to the final playback frame rate, but could be less if necessary
Compressing Raw Channels
Rotational data can usually be compressed to 16 bits with reasonable fidelity
Translations can be compressed similarly if they dont go too far from the origin
One can also store a float min & max value per channel and store a fixed point value per frame that interpolates between min & max
Lowering the frame rate will also save a lot of space, but can only be done for smooth animations
One could use an automatic algorithm to compress each channel individually based on user specified tolerances
Raw channels can also be stored using some form of delta compression
Keyframe Channels
Keyframe Channel
A channel can be stored as a sequence of keyframes
Each keyframe has a time and a value and usually some information describing the tangents at that location
The curves of the individual spans between the keys are defined by 1-D interpolation (usually piecewise Hermite)
Keyframe Channel
Keyframe
Time
Value
Tangent In
Tangent Out
Keyframe (time,value)
Keyframe Tangents
Keyframes are usually drawn so that the
incoming tangent points to the left (earlier in
time)
The arrow drawn is just for visual representation
and it should be remembered that if the two
arrows are exactly opposite, that actually means
the tangents are the same!
Also remember that we are only dealing with 1D
curves now, so the tangent really just a slope
Why Use Keyframes?
Good user interface for adjusting curves
Gives the user control over the value of the DOF and the velocity of the DOF
Define a perfectly smooth function (if desired)
Can offer good compression (not always)
Every animation system offers some variation on keyframing
Video games may consider keyframes for compression purposes, even though they have a performance cost
Animating with Keyframes
Keyframed channels form the foundation
for animating properties (DOFs) in many
commercial animation systems
Different systems use different variations
on the exact math but most are based on
some sort of cubic Hermite curves
Curve Fitting
Keyframes can be generated automatically from sampled data such as motion capture
This process is called curve fitting, as it involves finding curves that fit the data reasonably well
Fitting algorithms allow the user to specify tolerances that define the acceptable quality of the fit
This allows two way conversion between keyframe and raw formats, although the data might get slightly distorted with each translation
Keyframe Data Structure
class Keyframe {
float Time;
float Value;
float TangentIn,TangentOut;
char RuleIn,RuleOut; // Tangent rules
float A,B,C,D; // Cubic coefficients
}
Data Structures: Linked list
Doubly linked list
Array
Tangent Rules
Rather than store explicit numbers for tangents, it is often more convenient to store a rule and recompute the actual tangent as necessary
Usually, separate rules are stored for the incoming and outgoing tangents
Common rules for Hermite tangents include: Flat (tangent = 0)
Linear (tangent points to next/last key)
Smooth (automatically adjust tangent for smooth results)
Fixed (user can arbitrarily specify a value)
Remember that the tangent equals the rate of change of the DOF (or the velocity)
Note: I use v for tangents (velocity) instead of t which is used for time
Flat Tangents
Flat tangents are particularly useful for making
slow in and slow out motions (acceleration
from a stop and deceleration to a stop)
v = 0
Linear Tangents
(p0,t0)
v0out
v1in
(p1,t1)
01
0110
tt
ppvv inout
Smooth Tangents
(p1,t1) v1out
v1in
02
0211
tt
ppvv outin
(p2,t2)
(p0,t0)
Keep in mind that this wont work on the first or last tangent (just use the linear rule)
Step Tangent
Occasionally, one comes across the step tangent rule
This is a special case that just forces the entire span to a
constant
This requires hacking the cubic coefficients (a=b=c=0,
d=p0)
It can only be specified on the outgoing tangent and it
nullifies whatever rule is on the next incoming tangent
Cubic Coefficients
Keyframes are stored in order of their time
Between every two successive keyframes is a span of a cubic curve
The span is defined by the value of the two keyframes and the outgoing tangent of the first and incoming tangent of the second
Those 4 values are multiplied by the Hermite basis matrix and converted to cubic coefficients for the span
For simplicity, the coefficients can be stored in the first keyframe for each span
Cubic Equation (1 dimensional)
dctbtattf 23 cbtatdt
df 23 2
d
c
b
a
ttttf 123
d
c
b
a
ttdt
df0123 2
Hermite Curve (1D)
v1
p1 p0
v0
t0=0 t1=1
Hermite Curves
We want the value of the curve at t=0 to be f(0)=p0, and
at t=1, we want f(1)=p1
We want the derivative of the curve at t=0 to be v0, and
v1 at t=1
cbacbavf
ccbavf
dcbadcbapf
ddcbapf
23 1213 1
0203 0
111 1
000 0
2
1
2
0
23
1
23
0
Hermite Curves
d
c
b
a
v
v
p
p
cbav
cv
dcbap
dp
0123
0100
1111
1000
23
1
0
1
0
1
0
1
0
Matrix Form of Hermite Curve
1
0
1
0
1
0
1
0
1
0001
0100
1233
1122
0123
0100
1111
1000
v
v
p
p
d
c
b
a
v
v
p
p
d
c
b
a
Matrix Form of Hermite Curve
Remember, this assumes that t varies from 0 to 1
ct
gBt
tf
tf HrmHrm
1
0
1
0
23
0001
0100
1233
1122
1
v
v
p
p
ttttf
Inverse Linear Interpolation
If t0 is the time at the first key and t1 is the time of the second key, a linear interpolation of those times by parameter u would be:
The inverse of this operation gives us:
This gives us a 01 value on the span where we now will evaluate the cubic equation
Note: 1/(t1-t0) can be precomputed for each span
1010 1,, uttuttuLerpt
01
010 ,,
tt
tttttInvLerpu
Evaluating Cubic Spans
Tangents are generally expressed as a
slope of value/time
To normalize the spans to the 01 range,
we need to correct the tangents
So we must scale them by (t1-t0)
Precomputing Constants
For each span we pre-compute the cubic
coefficients:
101
001
1
0
0001
0100
1233
1122
vtt
vtt
p
p
d
c
b
a
Computing Cubic Coefficients
Note: My matrix34 class wont do this properly!
Actually, all of the 1s and 0s in the matrix make
it pretty easy to multiply it out by hand
101
001
1
0
0001
0100
1233
1122
vtt
vtt
p
p
d
c
b
a
Evaluating the Cubic
To evaluate the cubic equation for a span,
we must first turn our time t into a 0..1
value for the span (well call this
parameter u)
aubucuddcubuaux
tt
tttttInvLerpu
23
01
010 ,,
Channel::Precompute()
The two main setup computations a keyframe channel needs to perform are: Compute tangents from rules
Compute cubic coefficients from tangents & other data
This can be done in two separate passes through the keys or combined into one pass (but keep in mind there is some slightly tricky dependencies on the order that data must be processed if done in one pass)
Extrapolation Modes
Channels can specify extrapolation modes to define how the curve is extrapolated before tmin and after tmax
Usually, separate extrapolation modes can be set for before and after the actual data
Common choices: Constant value (hold first/last key value)
Linear (use tangent at first/last key)
Cyclic (repeat the entire channel)
Cyclic Offset (repeat with value offset)
Bounce (repeat alternating backwards & forwards)
Extrapolation
Note that extrapolation applies to the
entire channel and not to individual keys
In fact, extrapolation is not directly tied to
keyframing and can be used for any
method of channel storage (raw)
Extrapolation
Flat:
Linear:
tmin
tmax
Extrapolation
Cyclic:
Cyclic Offset:
Extrapolation
Bounce:
Keyframe Evaluation
The main runtime function for a channel is something like:
float Channel::Evaluate(float time);
This function will be called many times
For an input time t, there are 4 cases to consider: t is before the first key (use extrapolation)
t is after the last key (use extrapolation)
t falls exactly on some key (return key value)
t falls between two keys (evaluate cubic equation)
Channel::Evaluate()
The Channel::Evaluate function needs to
be very efficient, as it is called many times
while playing back animations
There are two main components to the
evaluation:
Find the proper span
Evaluate the cubic equation for the span
Random Access
To evaluate a channel at some arbitrary time t, we need to first find the proper span of the channel and then evaluate its equation
As the keyframes are irregularly spaced, this means we have to search for the right one
If the keyframes are stored as a linked list, there is little we can do except walk through the list looking for the right span
If they are stored in an array, we can use a binary search, which should do reasonably well
Finding the Span: Binary Search
A very reasonable way to find the key is by a binary search. This allows pretty fast (log N) access time with no additional storage cost (assuming keys are stored in an array (rather than a list))
Binary search is sometimes called divide and conquer or bisection
For even faster access, one could use hashing algorithms, but that is probably not necessary, as they require additional storage and most real channel accesses can take advantage of coherence (sequential access)
Finding the Span: Linear Search
One can always just loop through the keys from the beginning and look for the proper span
This is an acceptable place to start, as it is important to get things working properly before focusing on optimization
It may also be a reasonable option for interactive editing tools that would require key frames to be stored in a linked list
Of course, a bisection algorithm can probably be written in less than a dozen lines of code
Sequential Access
If a character is playing back an animation, then it will be accessing the channel data sequentially
Doing a binary search for each channel evaluation for each frame is not efficient for this
If we keep track of the most recently accessed key for each channel, then it is extremely likely that the next access will require either the same key or the very next one
This makes sequential access of keyframes potentially very fast
However there is a catch
Sequential Access
Consider a case where we have a video game with 20 bad guys running around
They all need to access the same animation data (which should only be stored once obviously)
However, they might each be accessing the channels with a different time
Therefore, the higher level code that plays animations needs to keep track of the most recent keys rather than the simpler solution of just having each channel just store a pointer to its most recent key
Thus, the animation player class needs to do considerable bookkeeping, as it will need to track a most recent key for every channel in the animation
High Performance Channels
If coefficients are stored, we can evaluate the cubic equation with 4 additions and 4 multiplies
In fact, a,b,c, & d can actually be precomputed to include the correction for 1/(t1-t0) so that the cubic can be directly solved for the original t. This reduces it to 3+ and 3*
In other words, evaluating the cubic is practically instantaneous, while jumping around through memory trying to locate the span is far worse
If we can take advantage of sequential access (which we usually can), we can reduce the span location to a very small number of operations
Robustness
The channel should always return some reasonable value regardless of what time t was passed in If there are no keys in the channel, it should just return 0
If there is just 1 key, it should return the value of that key
If there are more than 1 key, it should evaluate the curve or use an extrapolation rule if t is outside of the range
At a minimum, the constant extrapolation rule should be used, which just returns the value of the first (or last) key if t is before (or after) the keyframe range
When creating new keys or modifying the time of a key, one needs to verify that its time stays between the key before and after it
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